Assessing test suite effectiveness using static metrics

With the increasing amount of automated tests, we need ways to measure the test eectiveness. The state-of-the-art technique for assessing test eectiveness, mutation testing, is too slow and cumbersome to be used in large scale evolution studies or code audits by external companies. In this paper we investigated two alternatives, namely code coverage and assertion count. We discovered that code coverage outperforms assertion count by showing a relation with test suite eec-tiveness for all analysed project. Assertion count only displays such a relation in only one of the analysed projects. Further analysing this relationship between assertion count coverage and test eectiveness would allow to circumvent some of the problems of mutation testing.